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dc.contributor.authorParangusam, Kanakaraj
dc.contributor.authorLekshmana, Ramesh
dc.contributor.authorGoňo, Tomáš
dc.contributor.authorGoňo, Radomír
dc.date.accessioned2024-04-16T11:49:54Z
dc.date.available2024-04-16T11:49:54Z
dc.date.issued2023
dc.identifier.citationEnergies. 2023, vol. 16, issue 18, art. no. 6681.cs
dc.identifier.issn1996-1073
dc.identifier.urihttp://hdl.handle.net/10084/152504
dc.description.abstractElectricity demand has increased tremendously in recent years, due to the fact that all sectors require energy for their operation. Due to the increased amount of modern home appliances on the market, residential areas consume a significant amount of energy. This article focuses on the residential community to reduce peak load on residential distribution networks. Mostly, the residential consumer’s power demand increases more during the summer season due to many air conditioners (AC) operating in residential homes. This paper proposes a novel summer peak intelli gent controller (SPIC) algorithm to reduce summer peak load in residential distribution transformers (RDT). This proposed SPIC algorithm is implemented in a multi-home energy management system (MHEMS) with a four-home hardware prototype and a real-time TNEB system. This hardware prototype is divided into two different cases, one with and one without taking user comfort into account. When considering consumer comfort, all residential homes reduce their peak load almost equally. The maximum and minimum contribution percentages in Case 2 are 29.82% and 19.30%, respectively. Additionally, the real-time TNEB system is addressed in two different cases: with and without incentive-based programs. In the real-time TNEB system during peak hours, the novel SPIC algorithm reduces peak demand in Case 1 by 113.70 kW, and Case 2 further reduces it to 118.80 kW. The peak load decrease in Case 2 during peak hours is 4.5% greater than in Case 1. In addition, we conducted a residential consumer opinion survey to validate the acceptance rate of the proposed design and algorithm.cs
dc.language.isoencs
dc.publisherMDPIcs
dc.relation.ispartofseriesEnergiescs
dc.relation.urihttps://doi.org/10.3390/en16186681cs
dc.rights© 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license.cs
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/cs
dc.subjectmulti-home energy management system (MHEMS)cs
dc.subjectresidential distribution transformer (RDT)cs
dc.subjectsummer peak intelligent controller (SPIC)cs
dc.subjectdemand side management (DSM)cs
dc.subjectTamil Nadu Electricity Board (TNEB)cs
dc.subjectPythoncs
dc.subjectenergy managementcs
dc.titleEvolution of a summer peak intelligent controller (SPIC) for residential distribution networkscs
dc.typearticlecs
dc.identifier.doi10.3390/en16186681
dc.rights.accessopenAccesscs
dc.type.versionpublishedVersioncs
dc.type.statusPeer-reviewedcs
dc.description.sourceWeb of Sciencecs
dc.description.volume16cs
dc.description.issue18cs
dc.description.firstpageart. no. 6681cs
dc.identifier.wos001081857000001


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© 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license.
Except where otherwise noted, this item's license is described as © 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license.